A sensor protein was computationally designed and linked to gene components to enable a plant, Nicotiana tabacum, to display a loss of chlorophyll. - M.S. Antunes et al., PLOS ONE

In electronics, even the most advanced computer is just a complex arrangement of simple, modular parts that control specific functions; the same integrated circuit might be found in an iPhone, or in an aircraft. Colorado State University scientists are creating this same modularity in – wait for it – plants, by designing gene “circuits” that control specific plant characteristics – color, size, resistance to drought, you name it.

The relatively new, interdisciplinary field is synthetic biology – the design of genetic circuits, just like in electronics, that control different functions and can be easily placed in one organism or the next. Most of today’s synthetic biologists work with simple microorganisms, like E. coli or yeast.

A CSU team led by June Medford, professor of biology, and Ashok Prasad, associate professor of chemical and biological engineering, is doing the same thing, but in the much more complex biological world of plants.

“We are quantitatively analyzing the gene parts so we can make predictable functions,” Medford said. Using the cell phone analogy, “Apple didn’t go and reinvent a circuit to build the new iPhone; they took an existing circuit and tweaked it,” she said. “Once you have the quantification, and the device physics of the parts characterized, you can use a computer to tell you how to put them together.”

Plants in particular pose a special problem, Prasad added. “Not only is the biology much more complicated than single-celled microorganisms, they are also slow to grow and develop. As a consequence, just testing different genetic circuits becomes a major undertaking.”

Tackling this problem, they’ve invented a method of characterizing not one or two, but hundreds of genetic circuits at a time that control plant functions. They first had to create a blueprint for part construction – the cell parts that make up the eventual circuits. For the testing, they used protoplasts, which are plant cells whose walls have been removed, so they’re little blobs of cytoplasm.

The researchers’ new method, published in Nature Methods Nov. 16, will pave the way to develop and screen hundreds of genetic circuits, opening the door for rapid new developments in plant synthetic biology.

Protoplasts are delicate, though, so the engineers employed mathematical modeling that accounted for all the special properties of each protoplast. Carrying out intensive data analysis and simulations led them to isolate properties of single protoplasts – an unprecedented achievement.

They demonstrated their method with the plant Arabidopsis, with later validation in the food grain species Sorghum bicolor – demonstrating their technique with a commercially relevant species.

The scientists were supported by a Department of Energy grant for working on a specific circuit that, when completed, will act like a hard switch that turns on and off a specific genetic function.

Co-first author Katherine Schaumberg and co-author Wenlong Xu, both graduate students in biomedical engineering, handled all the data analysis for the project, and helped develop the mathematical model.

Co-first author and research assistant professor Mauricio Antunes helped develop the experimental platform for the protoplast experiments, while postdoctoral associates Tessema Kassaw and Christopher Zalewski also played crucial roles in experiments and analysis.

“This was a true collaboration in which both sides participated fully in the entire endeavor, and should be a model for collaborations between computational modelers and experimental biologists,” Prasad said.

The most accepted theory of the origin of the universe is still the Big Bang. The theory proposes the universe started from a small singularity (the gravitational kind), then began to expand over the succeeding 13.8 billion years. Although this expansion has its own issues, a bigger question remains: what preceded the Big Bang?

Physicists have created a quantum atomic clock that uses a new design to achieve unprecedented levels of accuracy and stability. Its broad range of potential applications could even stretch to research into dark matter.

For decades, astronomers have known that Supermassive Black Holes (SMBHs) reside at the center of most massive galaxies. These black holes, which range from being hundreds of thousands to billions of Solar masses, exert a powerful influence on surrounding matter and are believed to be the cause of Active Galactic Nuclei (AGN). For as long as astronomers have known about them, they have sought to understand how SMBHs form and evolve.

For decades, the predominant cosmological model used by scientists has been based on the theory that in addition to baryonic matter – aka. “normal” or “luminous” matter, which we can see – the Universe also contains a substantial amount of invisible mass. This “Dark Matter” accounts for roughly 26.8% of the mass of the Universe, whereas normal matter accounts for just 4.9%.

According to current estimates, there could be as many as 100 billion planets in the Milky Way Galaxy alone. Unfortunately, finding evidence of these planets is tough, time-consuming work. For the most part, astronomers are forced to rely on indirect methods that measure dips in a star’s brightness (the Transit Method) of Doppler measurements of the star’s own motion (the Radial Velocity Method).